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Ofir‐Geva S, Meilijson I, Frenkel‐Toledo S, Soroker N. Use of multi-perturbation Shapley analysis in lesion studies of functional networks: The case of upper limb paresis. Hum Brain Mapp 2023; 44:1320-1343. [PMID: 36206326 PMCID: PMC9921264 DOI: 10.1002/hbm.26105] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/07/2022] [Accepted: 09/19/2022] [Indexed: 11/07/2022] Open
Abstract
Understanding the impact of variation in lesion topography on the expression of functional impairments following stroke is important, as it may pave the way to modeling structure-function relations in statistical terms while pointing to constraints for adaptive remapping and functional recovery. Multi-perturbation Shapley-value analysis (MSA) is a relatively novel game-theoretical approach for multivariate lesion-symptom mapping. In this methodological paper, we provide a comprehensive explanation of MSA. We use synthetic data to assess the method's accuracy and perform parameter optimization. We then demonstrate its application using a cohort of 107 first-event subacute stroke patients, assessed for upper limb (UL) motor impairment (Fugl-Meyer Assessment scale). Under the conditions tested, MSA could correctly detect simulated ground-truth lesion-symptom relationships with a sensitivity of 75% and specificity of ~90%. For real behavioral data, MSA disclosed a strong hemispheric effect in the relative contribution of specific regions-of-interest (ROIs): poststroke UL motor function was mostly contributed by damage to ROIs associated with movement planning (supplementary motor cortex and superior frontal gyrus) following left-hemispheric damage (LHD) and by ROIs associated with movement execution (primary motor and somatosensory cortices and the ventral brainstem) following right-hemispheric damage (RHD). Residual UL motor ability following LHD was found to depend on a wider array of brain structures compared to the residual motor ability of RHD patients. The results demonstrate that MSA can provide a unique insight into the relative importance of different hubs in neural networks, which is difficult to obtain using standard univariate methods.
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Affiliation(s)
- Shay Ofir‐Geva
- Department of Neurological RehabilitationLoewenstein Rehabilitation Medical CenterRaananaIsrael
- Department of Rehabilitation Medicine, Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
| | - Isaac Meilijson
- School of Mathematical SciencesTel Aviv UniversityTel AvivIsrael
| | | | - Nachum Soroker
- Department of Neurological RehabilitationLoewenstein Rehabilitation Medical CenterRaananaIsrael
- Department of Rehabilitation Medicine, Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
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Ferkey DM, Sengupta P, L’Etoile ND. Chemosensory signal transduction in Caenorhabditis elegans. Genetics 2021; 217:iyab004. [PMID: 33693646 PMCID: PMC8045692 DOI: 10.1093/genetics/iyab004] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 01/05/2021] [Indexed: 12/16/2022] Open
Abstract
Chemosensory neurons translate perception of external chemical cues, including odorants, tastants, and pheromones, into information that drives attraction or avoidance motor programs. In the laboratory, robust behavioral assays, coupled with powerful genetic, molecular and optical tools, have made Caenorhabditis elegans an ideal experimental system in which to dissect the contributions of individual genes and neurons to ethologically relevant chemosensory behaviors. Here, we review current knowledge of the neurons, signal transduction molecules and regulatory mechanisms that underlie the response of C. elegans to chemicals, including pheromones. The majority of identified molecules and pathways share remarkable homology with sensory mechanisms in other organisms. With the development of new tools and technologies, we anticipate that continued study of chemosensory signal transduction and processing in C. elegans will yield additional new insights into the mechanisms by which this animal is able to detect and discriminate among thousands of chemical cues with a limited sensory neuron repertoire.
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Affiliation(s)
- Denise M Ferkey
- Department of Biological Sciences, University at Buffalo, The State University of New York, Buffalo, NY 14260, USA
| | - Piali Sengupta
- Department of Biology, Brandeis University, Waltham, MA 02454, USA
| | - Noelle D L’Etoile
- Department of Cell and Tissue Biology, University of California, San Francisco, CA 94143, USA
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Alizad-Rahvar AR, Sadeghi M. Ambiguity in logic-based models of gene regulatory networks: An integrative multi-perturbation analysis. PLoS One 2018; 13:e0206976. [PMID: 30458000 PMCID: PMC6245684 DOI: 10.1371/journal.pone.0206976] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 10/23/2018] [Indexed: 01/13/2023] Open
Abstract
Most studies of gene regulatory network (GRN) inference have focused extensively on identifying the interaction map of the GRNs. However, in order to predict the cellular behavior, modeling the GRN in terms of logic circuits, i.e., Boolean networks, is necessary. The perturbation techniques, e.g., knock-down and over-expression, should be utilized for identifying the underlying logic behind the interactions. However, we will show that by using only transcriptomic data obtained by single-perturbation experiments, we cannot observe all regulatory interactions, and this invisibility causes ambiguity in our model. Consequently, we need to employ the data of multiple omics layers (genome, transcriptome, and proteome) as well as multiple perturbation experiments to reduce or eliminate ambiguity in our modeling. In this paper, we introduce a multi-step perturbation experiment to deal with ambiguity. Moreover, we perform a thorough analysis to investigate which types of perturbations and omics layers play the most important role in the unambiguous modeling of the GRNs and how much ambiguity will be eliminated by considering more perturbations and more omics layers. Our analysis shows that performing both knock-down and over-expression is necessary in order to achieve the least ambiguous model. Moreover, the more steps of the perturbation are taken, the more ambiguity is eliminated. In addition, we can even achieve an unambiguous model of the GRN by using multi-step perturbation and integrating transcriptomic, protein-protein interaction, and cis-element data. Finally, we demonstrate the effect of utilizing different types of perturbation experiment and integrating multi-omics data on identifying the logic behind the regulatory interactions in a synthetic GRN. In conclusion, relying on the results of only knock-down experiments and not including as many omics layers as possible in the GRN inference, makes the results ambiguous, unreliable, and less accurate.
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Affiliation(s)
- Amir Reza Alizad-Rahvar
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- * E-mail: (ARA); (MS)
| | - Mehdi Sadeghi
- National Institute for Genetic Engineering and Biotechnology, Tehran, Iran
- * E-mail: (ARA); (MS)
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Cesari G, Algaba E, Moretti S, Nepomuceno JA. An application of the Shapley value to the analysis of co-expression networks. APPLIED NETWORK SCIENCE 2018; 3:35. [PMID: 30839839 PMCID: PMC6214322 DOI: 10.1007/s41109-018-0095-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 08/14/2018] [Indexed: 06/09/2023]
Abstract
We study the problem of identifying relevant genes in a co-expression network using a (cooperative) game theoretic approach. The Shapley value of a cooperative game is used to asses the relevance of each gene in interaction with the others, and to stress the role of nodes in the periphery of a co-expression network for the regulation of complex biological pathways of interest. An application of the method to the analysis of gene expression data from microarrays is presented, as well as a comparison with classical centrality indices. Finally, making further assumptions about the a priori importance of genes, we combine the game theoretic model with other techniques from cluster analysis.
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Affiliation(s)
- Giulia Cesari
- Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Encarnación Algaba
- Department of Applied Mathematics and IMUS, University of Seville, Seville, Spain
| | - Stefano Moretti
- Université Paris-Dauphine, PSL Research University, CNRS, LAMSADE, Paris, 75016 France
| | - Juan A. Nepomuceno
- Department of Computer Languages and Systems, University of Seville, Seville, Spain
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Neural correlates of visuospatial bias in patients with left hemisphere stroke: a causal functional contribution analysis based on game theory. Neuropsychologia 2018; 115:142-153. [DOI: 10.1016/j.neuropsychologia.2017.10.013] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 10/10/2017] [Accepted: 10/10/2017] [Indexed: 11/22/2022]
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Toba MN, Zavaglia M, Rastelli F, Valabrégue R, Pradat‐Diehl P, Valero‐Cabré A, Hilgetag CC. Game theoretical mapping of causal interactions underlying visuo-spatial attention in the human brain based on stroke lesions. Hum Brain Mapp 2017; 38:3454-3471. [PMID: 28419682 PMCID: PMC5645205 DOI: 10.1002/hbm.23601] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 03/22/2017] [Accepted: 03/23/2017] [Indexed: 01/08/2023] Open
Abstract
Anatomical studies conducted in neurological conditions have developed our understanding of the causal relationships between brain lesions and their clinical consequences. The analysis of lesion patterns extended across brain networks has been particularly useful in offering new insights on brain-behavior relationships. Here we applied multiperturbation Shapley value Analysis (MSA), a multivariate method based on coalitional game theory inferring causal regional contributions to specific behavioral outcomes from the characteristic functional deficits after stroke lesions. We established the causal patterns of contributions and interactions of nodes of the attentional orienting network on the basis of lesion and behavioral data from 25 right hemisphere stroke patients tested in visuo-spatial attention tasks. We calculated the percentage of damaged voxels for five right hemisphere cortical regions contributing to attentional orienting, involving seven specific Brodmann Areas (BA): Frontal Eye Fields, (FEF-BA6), Intraparietal Sulcus (IPS-BA7), Inferior Frontal Gyrus (IFG-BA44/BA45), Temporo-Parietal Junction (TPJ-BA39/BA40), and Inferior Occipital Gyrus (IOG-BA19). We computed the MSA contributions of these seven BAs to three behavioral clinical tests (line bisection, bells cancellation, and letter cancelation). Our analyses indicated IPS as the main contributor to the attentional orienting and also revealed synergistic influences among IPS, TPJ, and IOG (for bells cancellation and line bisection) and between TPJ and IFG (for bells and letter cancellation tasks). The findings demonstrate the ability of the MSA approach to infer plausible causal contributions of relevant right hemisphere sites in poststroke visuo-spatial attention and awareness disorders. Hum Brain Mapp 38:3454-3471, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Monica N. Toba
- Cerebral Dynamics, Plasticity and Rehabilitation Team, Frontlab, Brain and Spine Institute, ICMParisFrance
- Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F‐75013, & IHU‐A‐ICMParisFrance
- Laboratory of Functional Neurosciences (EA 4559)University Hospital of Amiens and University of Picardy Jules VerneAmiensFrance
| | - Melissa Zavaglia
- Department of Computational NeuroscienceUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- School of Engineering and ScienceJacobs University BremenGermany
| | - Federica Rastelli
- Cerebral Dynamics, Plasticity and Rehabilitation Team, Frontlab, Brain and Spine Institute, ICMParisFrance
- Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F‐75013, & IHU‐A‐ICMParisFrance
- AP‐HP, HxU Pitié‐Salpêtrière‐Charles‐Foix, service de Médecine Physique et de Réadaptation & PHRC Regional NEGLECTParisFrance
| | - Romain Valabrégue
- Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F‐75013, & IHU‐A‐ICMParisFrance
- Centre for NeuroImaging Research ‐ CENIR, Brain and Spine Institute, ICM, Paris, France
| | - Pascale Pradat‐Diehl
- AP‐HP, HxU Pitié‐Salpêtrière‐Charles‐Foix, service de Médecine Physique et de Réadaptation & PHRC Regional NEGLECTParisFrance
- GRC‐UPMC n° 18‐ Handicap cognitif et réadaptationParisFrance
| | - Antoni Valero‐Cabré
- Cerebral Dynamics, Plasticity and Rehabilitation Team, Frontlab, Brain and Spine Institute, ICMParisFrance
- Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F‐75013, & IHU‐A‐ICMParisFrance
- Laboratory for Cerebral Dynamics, Plasticity & Rehabilitation, Boston University School of MedicineBostonMassachusetts
- Cognitive Neuroscience and Information Technology Research Program, Open University of Catalonia (UOC)Barcelona08035Spain
| | - Claus C. Hilgetag
- Department of Computational NeuroscienceUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of Health SciencesBoston UniversityBostonMassachusetts
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Zavaglia M, Forkert ND, Cheng B, Gerloff C, Thomalla G, Hilgetag CC. Technical considerations of a game-theoretical approach for lesion symptom mapping. BMC Neurosci 2016; 17:40. [PMID: 27349961 PMCID: PMC4924231 DOI: 10.1186/s12868-016-0275-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 06/15/2016] [Indexed: 08/27/2023] Open
Abstract
Background Various strategies have been used for inferring brain functions from stroke lesions. We explored a new mathematical approach based on game theory, the so-called multi-perturbation Shapley value analysis (MSA), to assess causal function localizations and interactions from multiple perturbation data. We applied MSA to a dataset composed of lesion patterns of 148 acute stroke patients and their National Institutes of Health Stroke Scale (NIHSS) scores, to systematically investigate the influence of different parameter settings on the outcomes of the approach. Specifically, we investigated aspects of MSA methodology including the choice of the predictor algorithm (typology and kernel functions), training dataset (original versus binary), as well as the influence of lesion thresholds. We assessed the suitability of MSA for processing real clinical lesion data and established the central parameters for this analysis. Results We derived general recommendations for the analysis of clinical datasets by MSA and showed that, for the studied dataset, the best approach was to use a linear-kernel support vector machine predictor, trained with a binary training dataset, where the binarization was implemented through a median threshold of lesion size for each region. We demonstrated that the results obtained with different MSA variants lead to almost identical results as the basic MSA. Conclusions MSA is a feasible approach for the multivariate lesion analysis of clinical stroke data. Informed choices need to be made to set parameters that may affect the analysis outcome.
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Affiliation(s)
- Melissa Zavaglia
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany. .,School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, 28759, Bremen, Germany.
| | - Nils D Forkert
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany.,Department of Radiology and Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 4N1, Canada
| | - Bastian Cheng
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany
| | - Claus C Hilgetag
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany.,Department of Health Sciences, Boston University, 635 Commonwealth Ave., Boston, MA, 02215, USA
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8
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Zavaglia M, Forkert ND, Cheng B, Gerloff C, Thomalla G, Hilgetag CC. Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke. NEUROIMAGE-CLINICAL 2015; 9:83-94. [PMID: 26448908 PMCID: PMC4544394 DOI: 10.1016/j.nicl.2015.07.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Revised: 07/03/2015] [Accepted: 07/15/2015] [Indexed: 11/26/2022]
Abstract
Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a 'map of stroke'.
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Key Words
- CT, computer tomography
- DWI, diffusion weighted imaging
- Game-theory
- Lesion inference
- MAPP, Multi-Area Pattern Prediction
- MCA, middle cerebral artery
- MRI, magnetic resonance imaging
- MSA, Multi-perturbation Shapley value Analysis
- MVPA, Multi-Variate Pattern Analysis
- Multi-perturbation Shapley value Analysis (MSA)
- NIHSS
- NIHSS, National Institutes of Health Stroke Scale
- SVM, support vector machine
- VAL, voxel-based analysis of lesions
- VBM, voxel-based morphometry
- VLSC, VOI-based Lesion Symptom Correlation
- VLSM, Volume-based Lesion Symptom Mapping
- VOI, volume of interest
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Affiliation(s)
- Melissa Zavaglia
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany ; School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, Bremen 28759, Germany
| | - Nils D Forkert
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany ; Department of Radiology, Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada
| | - Bastian Cheng
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Claus C Hilgetag
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany ; Department of Health Sciences, Boston University, 635 Commonwealth Ave., Boston, MA 02215, USA
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Causal functional contributions and interactions in the attention network of the brain: an objective multi-perturbation analysis. Brain Struct Funct 2015; 221:2553-68. [PMID: 26002616 DOI: 10.1007/s00429-015-1058-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2014] [Accepted: 05/06/2015] [Indexed: 10/23/2022]
Abstract
Spatial attention is a prime example for the distributed network functions of the brain. Lesion studies in animal models have been used to investigate intact attentional mechanisms as well as perspectives for rehabilitation in the injured brain. Here, we systematically analyzed behavioral data from cooling deactivation and permanent lesion experiments in the cat, where unilateral deactivation of the posterior parietal cortex (in the vicinity of the posterior middle suprasylvian cortex, pMS) or the superior colliculus (SC) cause a severe neglect in the contralateral hemifield. Counterintuitively, additional deactivation of structures in the opposite hemisphere reverses the deficit. Using such lesion data, we employed a game-theoretical approach, multi-perturbation Shapley value analysis (MSA), for inferring functional contributions and network interactions of bilateral pMS and SC from behavioral performance in visual attention studies. The approach provides an objective theoretical strategy for lesion inferences and allows a unique quantitative characterization of regional functional contributions and interactions on the basis of multi-perturbations. The quantitative analysis demonstrated that right posterior parietal cortex and superior colliculus made the strongest positive contributions to left-field orienting, while left brain regions had negative contributions, implying that their perturbation may reverse the effects of contralateral lesions or improve normal function. An analysis of functional modulations and interactions among the regions revealed redundant interactions (implying functional overlap) between regions within each hemisphere, and synergistic interactions between bilateral regions. To assess the reliability of the MSA method in the face of variable and incomplete input data, we performed a sensitivity analysis, investigating how much the contribution values of the four regions depended on the performance of specific configurations and on the prediction of unknown performances. The results suggest that the MSA approach is sensitive to categorical, but insensitive to gradual changes in the input data. Finally, we created a basic network model that was based on the known anatomical interactions among cortical-tectal regions and reproduced the experimentally observed behavior in visual orienting. We discuss the structural organization of the network model relative to the causal modulations identified by MSA, to aid a mechanistic understanding of the attention network of the brain.
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The Function of Snodprot in the Cerato-Platanin Family fromDactylellina cionopagain Nematophagous Fungi. Biosci Biotechnol Biochem 2014; 76:1835-42. [DOI: 10.1271/bbb.120173] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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11
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Shingai R, Ichijo H, Wakabayashi T, Tanaka H, Ogurusu T. Chemotaxis behavior toward an odor is regulated by constant sodium chloride stimulus in Caenorhabditis elegans. Neurosci Res 2014; 81-82:51-4. [PMID: 24561276 DOI: 10.1016/j.neures.2014.02.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2013] [Revised: 01/26/2014] [Accepted: 02/03/2014] [Indexed: 12/01/2022]
Abstract
We studied the chemotaxis behavior of Caenorhabditis elegans toward a chemoattractant in the presence of background sensory stimulus. Chemotaxis toward an odor butanone was greater in the presence of sodium chloride (NaCl) than that without NaCl. By contrast, chemotaxis toward NaCl was not affected by a butanone background. The salt-sensing ASE neuron-deficient che-1(p674) mutants and worms with ASE genetically ablated showed high chemotaxis toward butanone, regardless of the presence of a NaCl background. Therefore, in wild-type worms, information from ASE in the absence of NaCl suppresses butanone chemotaxis, while the suppression is removed in the presence of NaCl.
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Affiliation(s)
- Ryuzo Shingai
- Laboratory of Bioscience, Faculty of Engineering, Iwate University, 4-3-5 Ueda, Morioka 020-8551, Japan.
| | - Hiroshi Ichijo
- Laboratory of Bioscience, Faculty of Engineering, Iwate University, 4-3-5 Ueda, Morioka 020-8551, Japan.
| | - Tokumitsu Wakabayashi
- Laboratory of Bioscience, Faculty of Engineering, Iwate University, 4-3-5 Ueda, Morioka 020-8551, Japan.
| | - Hidetoshi Tanaka
- Laboratory of Bioscience, Faculty of Engineering, Iwate University, 4-3-5 Ueda, Morioka 020-8551, Japan.
| | - Tarou Ogurusu
- Laboratory of Bioscience, Faculty of Engineering, Iwate University, 4-3-5 Ueda, Morioka 020-8551, Japan.
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Peymen K, Watteyne J, Frooninckx L, Schoofs L, Beets I. The FMRFamide-Like Peptide Family in Nematodes. Front Endocrinol (Lausanne) 2014; 5:90. [PMID: 24982652 PMCID: PMC4058706 DOI: 10.3389/fendo.2014.00090] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2014] [Accepted: 05/31/2014] [Indexed: 12/31/2022] Open
Abstract
In the three decades since the FMRFamide peptide was isolated from the mollusk Macrocallista nimbosa, structurally similar peptides sharing a C-terminal RFamide motif have been identified across the animal kingdom. FMRFamide-like peptides (FLPs) represent the largest known family of neuropeptides in invertebrates. In the phylum Nematoda, at least 32 flp-genes are classified, making the FLP system of nematodes unusually complex. The diversity of the nematode FLP complement is most extensively mapped in Caenorhabditis elegans, where over 70 FLPs have been predicted. FLPs have shown to be expressed in the majority of the 302 C. elegans neurons including interneurons, sensory neurons, and motor neurons. The vast expression of FLPs is reflected in the broad functional repertoire of nematode FLP signaling, including neuroendocrine and neuromodulatory effects on locomotory activity, reproduction, feeding, and behavior. In contrast to the many identified nematode FLPs, only few peptides have been assigned a receptor and there is the need to clarify the pathway components and working mechanisms of the FLP signaling network. Here, we review the diversity, distribution, and functions of FLPs in nematodes.
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Affiliation(s)
- Katleen Peymen
- Functional Genomics and Proteomics Group, Department of Biology, KU Leuven, Leuven, Belgium
| | - Jan Watteyne
- Functional Genomics and Proteomics Group, Department of Biology, KU Leuven, Leuven, Belgium
| | - Lotte Frooninckx
- Functional Genomics and Proteomics Group, Department of Biology, KU Leuven, Leuven, Belgium
| | - Liliane Schoofs
- Functional Genomics and Proteomics Group, Department of Biology, KU Leuven, Leuven, Belgium
| | - Isabel Beets
- Functional Genomics and Proteomics Group, Department of Biology, KU Leuven, Leuven, Belgium
- *Correspondence: Isabel Beets, Functional Genomics and Proteomics Group, Department of Biology, KU Leuven, Naamsestraat 59, Leuven 3000, Belgium e-mail:
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Abstract
Organisms have to continuously adapt to changing environmental conditions or undergo developmental transitions. To meet the accompanying change in metabolic demands, the molecular mechanisms of adaptation involve concerted interactions which ultimately induce a modification of the metabolic state, which is characterized by reaction fluxes and metabolite concentrations. These state transitions are the effect of simultaneously manipulating fluxes through several reactions. While metabolic control analysis has provided a powerful framework for elucidating the principles governing this orchestrated action to understand metabolic control, its applications are restricted by the limited availability of kinetic information. Here, we introduce structural metabolic control as a framework to examine individual reactions' potential to control metabolic functions, such as biomass production, based on structural modeling. The capability to carry out a metabolic function is determined using flux balance analysis (FBA). We examine structural metabolic control on the example of the central carbon metabolism of Escherichia coli by the recently introduced framework of functional centrality (FC). This framework is based on the Shapley value from cooperative game theory and FBA, and we demonstrate its superior ability to assign “share of control” to individual reactions with respect to metabolic functions and environmental conditions. A comparative analysis of various scenarios illustrates the usefulness of FC and its relations to other structural approaches pertaining to metabolic control. We propose a Monte Carlo algorithm to estimate FCs for large networks, based on the enumeration of elementary flux modes. We further give detailed biological interpretation of FCs for production of lactate and ATP under various respiratory conditions. Insight into the functioning of metabolic control to meet changing demands is a first step in rational engineering of biological systems towards a desired behavior. Metabolic control analysis provides the means to examine the impact of change of reaction fluxes on a specific target flux based on kinetic modeling, but suffers from limitations of the kinetic approach. Here, we introduce and analyze structural metabolic control as a framework to overcome these limitations. We utilize functional centrality, a framework based on the Shapley value from cooperative game theory and flux balance analysis, to determine the contribution of individual reactions to the functions accomplished by a metabolic network. These contributions, in turn, depend on the control exerted on the remaining network. Functional centrality provides the mathematical means to gain further understanding of metabolic control. The potential applications range from facilitating strategies of rational strain design to drug target identification.
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Natarajan M. Unsupervised Methods to Identify Cellular Signaling Networks from Perturbation Data. Bioinformatics 2013. [DOI: 10.4018/978-1-4666-3604-0.ch030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
The inference of cellular architectures from detailed time-series measurements of intracellular variables is an active area of research. High throughput measurements of responses to cellular perturbations are usually analyzed using a variety of machine learning methods that typically only work within one type of measurement. Here, summaries of some recent research attempts are presented–these studies have expanded the scope of the problem by systematically integrating measurements across multiple layers of regulation including second messengers, protein phosphorylation markers, transcript levels, and functional phenotypes into signaling vectors or signatures of signal transduction. Data analyses through simple unsupervised methods provide rich insight into the biology of the underlying network, and in some cases reconstruction of key architectures of the underlying network from perturbation data. The methodological advantages provided by these efforts are examined using data from a publicly available database of responses to systematic perturbations of cellular signaling networks generated by the Alliance for Cellular Signaling (AfCS).
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Sajitz-Hermstein M, Nikoloski Z. Restricted cooperative games on metabolic networks reveal functionally important reactions. J Theor Biol 2012; 314:192-203. [PMID: 22940237 DOI: 10.1016/j.jtbi.2012.08.018] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2011] [Revised: 08/02/2012] [Accepted: 08/16/2012] [Indexed: 11/26/2022]
Abstract
Understanding the emerging properties of complex biological systems is in the crux of systems biology studies. Computational methods for elucidating the role of each component in the synergetic interplay can be used to identify targets for genetic and metabolic engineering. In particular, we aim at determining the importance of reactions in a metabolic network with respect to a specific biological function. Therefore, we propose a novel game-theoretic framework which integrates restricted cooperative games with the outcome of flux balance analysis. We define productivity games on metabolic networks and present an analysis of their unrestricted and restricted variants based on the game-theoretic solution concept of the Shapley value. Correspondingly, this concept provides a characterization of the robustness and functional centrality for each enzyme involved in a given metabolic network. Furthermore, the comparison of two different environments - feast and famine - demonstrates the dependence of the results on the imposed flux capacities.
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Affiliation(s)
- Max Sajitz-Hermstein
- Systems Biology and Mathematical Modeling Group, Max-Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany.
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16
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Jacobs C, Segrè D. Organization Principles in Genetic Interaction Networks. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2012; 751:53-78. [DOI: 10.1007/978-1-4614-3567-9_3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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17
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Moretti S, Vasilakos AV. An overview of recent applications of Game Theory to bioinformatics. Inf Sci (N Y) 2010. [DOI: 10.1016/j.ins.2010.07.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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18
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Kaufman A, Serfaty C, Deouell LY, Ruppin E, Soroker N. Multiperturbation analysis of distributed neural networks: the case of spatial neglect. Hum Brain Mapp 2010; 30:3687-95. [PMID: 19449335 DOI: 10.1002/hbm.20797] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
This study assesses the feasibility of using a multiperturbation analysis (MPA) approach for lesion-symptom mapping. We analyze the relative contribution of damage in different brain regions to the expression of spatial neglect, as revealed in line-bisection performance. The data set comprised of normalized lesion information and bisection test results from 23 first-event right-hemisphere stroke patients. Obtaining quantitative measures of task relevance for different regions of interest (ROIs), the following ROIs were found to be the most contributing: the supramarginal and angular gyri of the inferior parietal lobule, the superior parietal lobule, the anterior part of the temporo-parietal junction connecting the superior temporal and supramarginal gyri, and the thalamus. MPA is likely to play an important role in elucidating the anatomical substrate of complex functions.
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Affiliation(s)
- Alon Kaufman
- Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel.
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Elucidating regulatory mechanisms downstream of a signaling pathway using informative experiments. Mol Syst Biol 2009; 5:287. [PMID: 19584836 PMCID: PMC2724975 DOI: 10.1038/msb.2009.45] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2008] [Accepted: 05/26/2009] [Indexed: 11/25/2022] Open
Abstract
Signaling cascades are triggered by environmental stimulation and propagate the signal to regulate transcription. Systematic reconstruction of the underlying regulatory mechanisms requires pathway-targeted, informative experimental data. However, practical experimental design approaches are still in their infancy. Here, we propose a framework that iterates design of experiments and identification of regulatory relationships downstream of a given pathway. The experimental design component, called MEED, aims to minimize the amount of laboratory effort required in this process. To avoid ambiguity in the identification of regulatory relationships, the choice of experiments maximizes diversity between expression profiles of genes regulated through different mechanisms. The framework takes advantage of expert knowledge about the pathways under study, formalized in a predictive logical model. By considering model-predicted dependencies between experiments, MEED is able to suggest a whole set of experiments that can be carried out simultaneously. Our framework was applied to investigate interconnected signaling pathways in yeast. In comparison with other approaches, MEED suggested the most informative experiments for unambiguous identification of transcriptional regulation in this system.
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Andersen J, Krichevsky A, Leheste JR, Moloney DJ. Caenorhabditis elegans as an undergraduate educational tool for teaching RNAi. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2008; 36:417-427. [PMID: 21591231 DOI: 10.1002/bmb.20233] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Discovery of RNA-mediated interference (RNAi) is widely recognized as one of the most significant molecular biology breakthroughs in the past 10 years. There is a need for science educators to develop teaching tools and laboratory activities that demonstrate the power of this new technology and help students to better understand the RNAi process. C. elegans is an ideal model organism for the undergraduate laboratory because of the simplicity of worm maintenance, its well-studied genetic background, and the fact that it can be employed as a model organism in laboratory environments where vertebrate research is restricted. Certain unique features of C. elegans make it a very suitable organism for RNAi studies. Specifically, nematode strains highly sensitive to RNAi are readily available from public sources, and RNAi induction by a feeding method is an uncomplicated procedure that lends itself readily as an educational tool. In this article, we provide a detailed depiction of the use of C. elegans as an RNAi educational tool, describing two separate RNAi-based experiments. One is a qualitative experiment where students can examine the effects of knocking down the unc-22 gene involved in the regulation of muscle contraction, which results in a "twitching" phenotype. The other experiment is a quantitative RNAi experiment, where students measure the effect of knocking down the lsy-2 gene involved in neuronal development. Although these experiments are designed for a college-level study, nematode research projects can also be accomplished in secondary school facilities.
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Affiliation(s)
- Janet Andersen
- Department of Biochemistry and Cellular Biology, Center for Science and Mathematics Education, Stony Brook University, Stony Brook, New York 11794-5215.
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Moretti S, van Leeuwen D, Gmuender H, Bonassi S, van Delft J, Kleinjans J, Patrone F, Merlo DF. Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution. BMC Bioinformatics 2008; 9:361. [PMID: 18764936 PMCID: PMC2556684 DOI: 10.1186/1471-2105-9-361] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2008] [Accepted: 09/02/2008] [Indexed: 02/04/2023] Open
Abstract
Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways.
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Affiliation(s)
- Stefano Moretti
- Epidemiology and Biostatistics, National Cancer Research Institute, Genova, Italy.
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Models from experiments: combinatorial drug perturbations of cancer cells. Mol Syst Biol 2008; 4:216. [PMID: 18766176 PMCID: PMC2564730 DOI: 10.1038/msb.2008.53] [Citation(s) in RCA: 139] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2007] [Accepted: 07/14/2008] [Indexed: 12/26/2022] Open
Abstract
We present a novel method for deriving network models from molecular profiles of perturbed cellular systems. The network models aim to predict quantitative outcomes of combinatorial perturbations, such as drug pair treatments or multiple genetic alterations. Mathematically, we represent the system by a set of nodes, representing molecular concentrations or cellular processes, a perturbation vector and an interaction matrix. After perturbation, the system evolves in time according to differential equations with built-in nonlinearity, similar to Hopfield networks, capable of representing epistasis and saturation effects. For a particular set of experiments, we derive the interaction matrix by minimizing a composite error function, aiming at accuracy of prediction and simplicity of network structure. To evaluate the predictive potential of the method, we performed 21 drug pair treatment experiments in a human breast cancer cell line (MCF7) with observation of phospho-proteins and cell cycle markers. The best derived network model rediscovered known interactions and contained interesting predictions. Possible applications include the discovery of regulatory interactions, the design of targeted combination therapies and the engineering of molecular biological networks.
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Deutscher D, Meilijson I, Schuster S, Ruppin E. Can single knockouts accurately single out gene functions? BMC SYSTEMS BIOLOGY 2008; 2:50. [PMID: 18564419 PMCID: PMC2443110 DOI: 10.1186/1752-0509-2-50] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2008] [Accepted: 06/18/2008] [Indexed: 11/14/2022]
Abstract
Background When analyzing complex biological systems, a major objective is localization of function – assessing how much each element contributes to the execution of specific tasks. To establish causal relationships, knockout and perturbation studies are commonly executed. The vast majority of studies perturb a single element at a time, yet one may hypothesize that in non-trivial biological systems single-perturbations will fail to reveal the functional organization of the system, owing to interactions and redundancies. Results We address this fundamental gap between theory and practice by quantifying how misleading the picture arising from classical single-perturbation analysis is, compared with the full multiple-perturbations picture. To this end we use a combination of a novel approach for quantitative, rigorous multiple-knockouts analysis based on the Shapley value from game theory, with an established in-silico model of Saccharomyces cerevisiae metabolism. We find that single-perturbations analysis misses at least 33% of the genes that contribute significantly to the growth potential of this organism, though the essential genes it does find are responsible for most of the growth potential. But when assigning gene contributions for individual metabolic functions, the picture arising from single-perturbations is severely lacking and a multiple-perturbations approach turns out to be essential. Conclusion The multiple-perturbations investigation yields a significantly richer and more biologically plausible functional annotation of the genes comprising the metabolic network of the yeast.
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Stevenson M. Highlights of the 15th Conference on Retroviruses and Opportunistic Infections. Basic science summary. TOPICS IN HIV MEDICINE : A PUBLICATION OF THE INTERNATIONAL AIDS SOCIETY, USA 2008; 16:1-5. [PMID: 18441376 DOI: 10.1007/s11750-008-0044-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
The scientific advances made in the year leading up to the 15th Conference on Retroviruses and Opportunistic Infections were overshadowed, to some extent, by setbacks in the AIDS vaccine research arena and in particular, the failure of the Merck STEP trial. Arguably, these disappointments were offset by strong advances that were being made in basic science and pathogenesis. In particular, recent discoveries into cellular factors that influence virus-host cell interplay and new insights into the mechanisms of viral pathogenesis were highlighted at the meeting. These research discoveries paint an optimistic picture regarding the development of new strategies to combat HIV and AIDS.
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Affiliation(s)
- Mario Stevenson
- Program in Molecular Medicine and Department of Molecular Genetics and Microbiology, University of Massachusetts Medical School, Worcester, MA, USA
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Behre J, Wilhelm T, von Kamp A, Ruppin E, Schuster S. Structural robustness of metabolic networks with respect to multiple knockouts. J Theor Biol 2007; 252:433-41. [PMID: 18023456 DOI: 10.1016/j.jtbi.2007.09.043] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2007] [Revised: 09/21/2007] [Accepted: 09/26/2007] [Indexed: 10/22/2022]
Abstract
We present a generalised framework for analysing structural robustness of metabolic networks, based on the concept of elementary flux modes (EFMs). Extending our earlier study on single knockouts [Wilhelm, T., Behre, J., Schuster, S., 2004. Analysis of structural robustness of metabolic networks. IEE Proc. Syst. Biol. 1(1), 114-120], we are now considering the general case of double and multiple knockouts. The robustness measures are based on the ratio of the number of remaining EFMs after knockout vs. the number of EFMs in the unperturbed situation, averaged over all combinations of knockouts. With the help of simple examples we demonstrate that consideration of multiple knockouts yields additional information going beyond single-knockout results. It is proven that the robustness score decreases as the knockout depth increases. We apply our extended framework to metabolic networks representing amino acid anabolism in Escherichia coli and human hepatocytes, and the central metabolism in human erythrocytes. Moreover, in the E. coli model the two subnetworks synthesising amino acids that are essential and those that are non-essential for humans are studied separately. The results are discussed from an evolutionary viewpoint. We find that E. coli has the most robust metabolism of all the cell types studied here. Considering only the subnetwork of the synthesis of non-essential amino acids, E. coli and the human hepatocyte show about the same robustness.
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Affiliation(s)
- Jörn Behre
- Faculty of Biology and Pharmaceutics, Section of Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-07743 Jena, Germany.
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Kaufman A, Dror G, Meilijson I, Ruppin E. Gene expression of Caenorhabditis elegans neurons carries information on their synaptic connectivity. PLoS Comput Biol 2007; 2:e167. [PMID: 17154715 PMCID: PMC1676027 DOI: 10.1371/journal.pcbi.0020167] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2006] [Accepted: 10/26/2006] [Indexed: 01/28/2023] Open
Abstract
The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting opportunity to approach this question in a large-scale quantitative manner. Its synaptic connectivity network has been identified, and, combined with cellular studies, we currently have characteristic connectivity and gene expression signatures for most of its neurons. By using two complementary analysis assays we show that the expression signature of a neuron carries significant information about its synaptic connectivity signature, and identify a list of putative genes predicting neural connectivity. The current study rigorously quantifies the relation between gene expression and synaptic connectivity signatures in the C. elegans nervous system and identifies subsets of neurons where this relation is highly marked. The results presented and the genes identified provide a promising starting point for further, more detailed computational and experimental investigations. The study of the genetic basis of the formation of neural connections in the nervous system (synaptogenesis) has been at the forefront of recent investigations in neuroscience. With the advancement of molecular biology research, many small-scale studies have identified specific genes and mechanisms involved in axon guidance and synaptogenesis. The nematode C. elegans provides an exciting opportunity to approach these issues in a computational large-scale manner. Its synaptic connectivity network has been identified, and, combined with information from gene expression studies, we now have neuronal connectivity and gene expression signatures for most of its neurons. Analyzing this data, Kaufman and colleagues show that the expression signature of a neuron carries significant information about its synaptic connectivity and can predict its neural targets in a statistically significant manner. The current study is the first, to our knowledge, to rigorously quantify and measure this relation. It identifies a putative list of genes that specify the neurons' connections which nicely conforms with the existing literature and leads to interesting new predictions.
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Affiliation(s)
- Alon Kaufman
- Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel
- * To whom correspondence should be addressed. E-mail: (AK); (ER)
| | - Gideon Dror
- School of Computer Science, The Academic College of Tel Aviv–Yaffo, Tel Aviv, Israel
| | - Isaac Meilijson
- School of Mathematical Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Eytan Ruppin
- School of Computer Science and School of Medicine, Tel Aviv University, Tel Aviv, Israel
- * To whom correspondence should be addressed. E-mail: (AK); (ER)
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